Indexado en Registry

claude-usage-analyst

Precio sin confirmar★ 1,375 Estrellas de GitHubRegistro actualizado · 3 sept 2026agent-skill

Resumen

Analyze Claude Code and Claude Desktop Code token usage, cost, quota burn, model mix, cache read/write, and 5-hour block consumption using ccusage evidence. Use when the user asks why Claude quota was exhausted, whether a model such as fable/opus/sonnet is unusually expensive, how many tokens were spent today or historically, or needs a human-friendly explanation of local Claude Code CLI/Desktop usage.

Leer documentación completa

Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.

Claude Usage Analyst

Overview

Use this skill to produce evidence-based usage explanations from local ccusage data. Separate observed numbers from interpretation, and explain quota burn in human terms.

Workflow

Verify ccusage is available:
```
ccusage --version
```
If missing, install or update with npm install -g ccusage@latest or run with npx ccusage@latest.
Run the bundled analyzer for the requested window:
```
python3 /path/to/claude-usage-analyst/scripts/analyze_claude_usage.py \
  --since YYYY-MM-DD --until YYYY-MM-DD --timezone Asia/Shanghai
```
Default --since/--until is today in the selected timezone. For historical comparison, set --since to an earlier date such as the first day of the month; otherwise rank/median fields only describe the single target day.

If the user asks about a specific model comparison, pass aliases:

python3 scripts/analyze_claude_usage.py --model-a fable --model-b opus-4-8

Read references/explanation-guide.md when writing the final answer.

Evidence Rules

Base numeric claims on ccusage output or the bundled analyzer output.
State the scope: ccusage claude measures local Claude Code usage logs, including Claude Desktop's Claude Code sessions when those local logs exist. It is not a complete ordinary Claude.ai chat bill.
Report dates with timezone.
Explain cache clearly: cache read tokens are still usage/quota pressure even though the user did not type those words.
Do not infer Anthropic plan quota rules from local token counts unless the user provides plan details. Say "quota-like pressure" or "ccusage estimated cost/token burn" when exact plan accounting is unknown.
When comparing models, compare both token volume and estimated cost. A model can have similar token volume but higher cost.

Output Shape

Use this structure unless the user asks otherwise:

Short conclusion in plain language.
Evidence table: total tokens, cost, input, output, cache create, cache read.
Model comparison table.
5-hour block table when quota exhaustion is discussed.
Explanation of why the burn happened.
Confidence and caveats.

Keep the answer readable for non-technical users. Avoid unexplained terms like "cache read" without a one-sentence translation.

Ver fuente ↗

Metadatos del archivo

name: claude-usage-analyst
description: Analyze Claude Code and Claude Desktop Code token usage, cost, quota burn, model mix, cache read/write, and 5-hour block consumption using ccusage evidence. Use when the user asks why Claude quota was exhausted, whether a model such as fable/opus/sonnet is unusually expensive, how many tokens were spent today or historically, or needs a human-friendly explanation of local Claude Code CLI/Desktop usage.

Ver texto original

---
name: claude-usage-analyst
description: Analyze Claude Code and Claude Desktop Code token usage, cost, quota burn, model mix, cache read/write, and 5-hour block consumption using ccusage evidence. Use when the user asks why Claude quota was exhausted, whether a model such as fable/opus/sonnet is unusually expensive, how many tokens were spent today or historically, or needs a human-friendly explanation of local Claude Code CLI/Desktop usage.
---

# Claude Usage Analyst

## Overview

Use this skill to produce evidence-based usage explanations from local `ccusage` data. Separate observed numbers from interpretation, and explain quota burn in human terms.

## Workflow

1. Verify `ccusage` is available:
```bash
ccusage --version
```
If missing, install or update with `npm install -g ccusage@latest` or run with `npx ccusage@latest`.

2. Run the bundled analyzer for the requested window:
```bash
python3 /path/to/claude-usage-analyst/scripts/analyze_claude_usage.py \
--since YYYY-MM-DD --until YYYY-MM-DD --timezone Asia/Shanghai
```
Default `--since/--until` is today in the selected timezone.
For historical comparison, set `--since` to an earlier date such as the first day of the month; otherwise rank/median fields only describe the single target day.

3. If the user asks about a specific model comparison, pass aliases:
```bash
python3 scripts/analyze_claude_usage.py --model-a fable --model-b opus-4-8
```

4. Read `references/explanation-guide.md` when writing the final answer.

## Evidence Rules

- Base numeric claims on `ccusage` output or the bundled analyzer output.
- State the scope: `ccusage claude` measures local Claude Code usage logs, including Claude Desktop's Claude Code sessions when those local logs exist. It is not a complete ordinary Claude.ai chat bill.
- Report dates with timezone.
- Explain cache clearly: cache read tokens are still usage/quota pressure even though the user did not type those words.
- Do not infer Anthropic plan quota rules from local token counts unless the user provides plan details. Say "quota-like pressure" or "ccusage estimated cost/token burn" when exact plan accounting is unknown.
- When comparing models, compare both token volume and estimated cost. A model can have similar token volume but higher cost.

## Output Shape

Use this structure unless the user asks otherwise:

1. Short conclusion in plain language.
2. Evidence table: total tokens, cost, input, output, cache create, cache read.
3. Model comparison table.
4. 5-hour block table when quota exhaustion is discussed.
5. Explanation of why the burn happened.
6. Confidence and caveats.

Keep the answer readable for non-technical users. Avoid unexplained terms like "cache read" without a one-sentence translation.

Revisar el código fuente

Precio y costes de ejecución

Obtener el skill: Precio sin confirmar
Ejecutarlo: Requisitos sin confirmar. Consulta los costes del agente, API y servicios en la fuente.
Licencia: MIT
Precio sin confirmar: No hemos confirmado el precio. Los enlaces existentes al código y a la instalación siguen disponibles.

Obtener gratis no significa ejecutar gratis. El precio no es una evaluación de seguridad. Enviar información de precio →

Fuente del skill registrada

La ruta de instrucciones está registrada. No implica pruebas de ejecución, seguridad ni compatibilidad.

Revisar antes de instalar: Evitar instalación automática

Licencia: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
SKILL.md uses a placeholder path `/path/to/claude-usage-analyst/scripts/analyze_claude_usage.py`, which will fail unless the agent resolves the actual skill directory.
No sample output or test fixture is included, making it harder to verify the analyzer behaves correctly across environments.
The skill instructs installing `ccusage` globally with npm, which requires appropriate user permissions; this is acceptable but should be called out as an environment-changing step.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Abrir auditoría completa

Las herramientas son indicios de metadatos, no compatibilidad probada. Los prompts son sugerencias.

Empieza con una tarea pequeña

1Lee la fuente y confirma entradas, resultados, dependencias y permisos.
2Pide un plan al agente. Aprueba la configuración y los costes antes de probar en un entorno aislado.
3Comprueba resultados y archivos modificados. Informa solo de lo ejecutado y conserva la revisión de la fuente.

Consulta dependencias, claves API y costes externos en la fuente. Un repositorio público no implica servicios gratuitos.

Fuente y notas de uso

Indexado

Los metadatos y revisiones son orientativos. Popularidad, descubrimiento y ejecución correcta son hechos distintos.

Repositorio fuente: daymade/claude-code-skills
Licencia: MIT
Versión: 1.0.0
Último push de GitHub: 3 sept 2026
Registro actualizado: 3 sept 2026
Ruta de instrucciones: daymade-claude-code/claude-usage-analyst/SKILL.md @ 3717e0fbbafa

Versión declarada en el registro; consulta las versiones de la fuente.

Calidad

75/100

Sólido

Confianza

60/100

Solo sandbox

Auditoría

76/100

Requiere revisión

Abrir auditoría completa Ver informe de evaluación

Dependency or permission surface needs review
Permission surface may require sandboxing
SKILL.md uses a placeholder path `/path/to/claude-usage-analyst/scripts/analyze_claude_usage.py`, which will fail unless the agent resolves the actual skill directory.
No sample output or test fixture is included, making it harder to verify the analyzer behaves correctly across environments.
The skill instructs installing `ccusage` globally with npm, which requires appropriate user permissions; this is acceptable but should be called out as an environment-changing step.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
Resultados: —

Copiar no es instalar. Los recuentos requieren un informe de instalación correcta, no garantizan calidad general.

Acceso para agentes

La API Registry expone señales de decisión, confianza, auditoría, casos de uso e instalación sin raspar la interfaz.

Abrir API de instalación Formato de texto LLM Abrir Manifest Plan de resolución automática

Más detalles

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Creador: daymade
Fuente: daymade/claude-code-skills
Indexado por: Índice comunitario de OpenAgentSkill

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Esta ficha Indexado por Registry se atribuye a daymade, pero aún no está marcada como oficial. Reclámala para añadir una señal de propietario verificado y hacer más fiables futuras actualizaciones de lanzamiento, instalación y auditoría.

Kit para compartir

Kit de enlaces para creadores

Añade las insignias de evidencia a tu README

Muestra la ficha canónica, las señales actuales de confianza y auditoría, y evidencia real de Agent-Proven donde los desarrolladores evalúan el repositorio.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/daymade-claude-usage-analyst?metric=listed&label=Listed)](https://www.openagentskill.com/skills/daymade-claude-usage-analyst?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/daymade-claude-usage-analyst?metric=trust&label=Trust)](https://www.openagentskill.com/skills/daymade-claude-usage-analyst?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/daymade-claude-usage-analyst?metric=audit&label=Audit)](https://www.openagentskill.com/skills/daymade-claude-usage-analyst/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/daymade-claude-usage-analyst?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/daymade-claude-usage-analyst?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

Vista previa de insignia Abrir auditoría Kit para creadores

Señal de comunidad

Comparte si este skill resulta útil para tu flujo de Agent. Los comentarios agregados mejoran la clasificación con el tiempo.